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Automatic Control, IEEE Transactions on

Issue 11 • Date Nov. 2009

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Displaying Results 1 - 25 of 36
  • Table of contents

    Page(s): C1 - C4
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    Freely Available from IEEE
  • IEEE Transactions on Automatic Control publication information

    Page(s): C2
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    Freely Available from IEEE
  • Scanning the issue

    Page(s): 2489 - 2490
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  • In Memoriam for Michael K. Sain

    Page(s): 2491 - 2492
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    Freely Available from IEEE
  • Continuity of Varying-Feature-Set Control Laws

    Page(s): 2493 - 2505
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (944 KB) |  | HTML iconHTML  

    Classical sensor-based control laws are based on the regulation of a set of features to a desired reference value. In this paper, we focus on the study of control laws whose feature set varies during the servo. In that case, we first show that the classical control laws that use an iterative least-square minimization are discontinuous. We then show that these discontinuities are due to the pseudo-inverse operator, which is not continuous at matrix rank change. To solve this problem, we propose a new inversion operator. This operator is equal to the classical pseudo-inverse operator in the continuous cases, and ensures the continuity everywhere. This operator is then used to build a new control law. This general control scheme is applied to visual servoing, in order to ensure the continuity of the control law when some visual features leave the camera field of view. The experiments prove the interest and the validity of our approach. View full abstract»

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  • On Distributed Averaging Algorithms and Quantization Effects

    Page(s): 2506 - 2517
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (443 KB) |  | HTML iconHTML  

    We consider distributed iterative algorithms for the averaging problem over time-varying topologies. Our focus is on the convergence time of such algorithms when complete (unquantized) information is available, and on the degradation of performance when only quantized information is available. We study a large and natural class of averaging algorithms, which includes the vast majority of algorithms proposed to date, and provide tight polynomial bounds on their convergence time. We also describe an algorithm within this class whose convergence time is the best among currently available averaging algorithms for time-varying topologies. We then propose and analyze distributed averaging algorithms under the additional constraint that agents can only store and communicate quantized information, so that they can only converge to the average of the initial values of the agents within some error. We establish bounds on the error and tight bounds on the convergence time, as a function of the number of quantization levels. View full abstract»

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  • Multirate Sampled-Data Output Feedback Control With Application to Smart Material Actuated Systems

    Page(s): 2518 - 2529
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (671 KB) |  | HTML iconHTML  

    We consider multirate sampled-data output feedback control of a class of nonlinear systems using high-gain observers where the measurement sampling rate is made faster than the control update rate. We show that, in the presence of bounded disturbances, given a sampled data state feedback controller that achieves stabilization with respect to a closed set, the multirate output feedback controller recovers stabilization of the same set provided the measurement sampling rate is sufficiently fast. As an application we consider the control of smart material actuated systems. This scheme combines a discrete-time high-gain observer with a hysteresis inversion controller where the hysteresis is modeled using a Preisach operator. Experimental results for the control of a shape memory alloy actuated rotary joint are provided. View full abstract»

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  • The Series Product and Its Application to Quantum Feedforward and Feedback Networks

    Page(s): 2530 - 2544
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (492 KB) |  | HTML iconHTML  

    The purpose of this paper is to present simple and general algebraic methods for describing series connections in quantum networks. These methods build on and generalize existing methods for series (or cascade) connections by allowing for more general interfaces, and by introducing an efficient algebraic tool, the series product. We also introduce another product, which we call the concatenation product, that is useful for assembling and representing systems without necessarily having connections. We show how the concatenation and series products can be used to describe feedforward and feedback networks. A selection of examples from the quantum control literature are analyzed to illustrate the utility of our network modeling methodology. View full abstract»

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  • Randomized Strategies for Probabilistic Solutions of Uncertain Feasibility and Optimization Problems

    Page(s): 2545 - 2559
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (636 KB) |  | HTML iconHTML  

    In this paper, we study two general semi-infinite programming problems by means of a randomized strategy based on statistical learning theory. The sample size results obtained with this approach are generally considered to be very conservative by the control community. The first main contribution of this paper is to demonstrate that this is not necessarily the case. Utilizing as a starting point one-sided results from statistical learning theory, we obtain bounds on the number of required samples that are manageable for ldquoreasonablerdquo values of probabilistic confidence and accuracy. In particular, we show that the number of required samples grows with the accuracy parameter epsiv as 1/epsivln 1/epsiv , and this is a significant improvement when compared to the existing bounds which depend on 1/epsiv2ln 1/epsiv2. Secondly, we present new results for optimization and feasibility problems involving Boolean expressions consisting of polynomials. In this case, when the accuracy parameter is sufficiently small, an explicit bound that only depends on the number of decision variables, and on the confidence and accuracy parameters is presented. For convex optimization problems, we also prove that the required sample size is inversely proportional to the accuracy for fixed confidence. Thirdly, we propose a randomized algorithm that provides a probabilistic solution circumventing the potential conservatism of the bounds previously derived. View full abstract»

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  • Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics

    Page(s): 2560 - 2572
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (924 KB) |  | HTML iconHTML  

    In this paper, we address the problem of driving a group of agents towards a consensus point when the agents have a discrete-time single- or double-integrator dynamics and the communication network is time-varying. We propose decentralized model predictive control schemes that take into account constraints on the agents' input and show that they guarantee consensus under mild assumptions. Since the global cost does not decrease monotonically, it cannot be used as a Lyapunov function for proving convergence to consensus. For this reason, our proofs exploit geometric properties of the optimal path followed by individual agents. View full abstract»

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  • Optimized Scheduled Multiple Access Control for Wireless Sensor Networks

    Page(s): 2573 - 2585
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (688 KB) |  | HTML iconHTML  

    We consider wireless sensor networks with multiple sensor modalities that capture data to be transported over multiple frequency channels to potentially multiple gateways. We study a general problem of maximizing a utility function of achievable transmission rates between communicating nodes. Decisions involve routing, transmission scheduling, power control, and channel selection, while constraints include physical communication constraints, interference constraints, and fairness constraints. Due to its structure the formulation grows exponentially with the size of the network. Drawing upon large-scale decomposition ideas in mathematical programming, we develop a cutting-plane algorithm and show that it terminates in a finite number of iterations. Every iteration requires the solution of a subproblem which is NP-hard. To solve the subproblem we i) devise a particular relaxation that is solvable in polynomial time and ii) leverage polynomial-time approximation schemes. A combination of both approaches enables an improved decomposition algorithm which is efficient for solving large problem instances. View full abstract»

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  • On Krause's Multi-Agent Consensus Model With State-Dependent Connectivity

    Page(s): 2586 - 2597
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (920 KB) |  | HTML iconHTML  

    We study a model of opinion dynamics introduced by Krause: each agent has an opinion represented by a real number, and updates its opinion by averaging all agent opinions that differ from its own by less than one. We give a new proof of convergence into clusters of agents, with all agents in the same cluster holding the same opinion. We then introduce a particular notion of equilibrium stability and provide lower bounds on the inter-cluster distances at a stable equilibrium. To better understand the behavior of the system when the number of agents is large, we also introduce and study a variant involving a continuum of agents, obtaining partial convergence results and lower bounds on inter-cluster distances, under some mild assumptions. View full abstract»

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  • Time-Minimal Control of Dissipative Two-Level Quantum Systems: The Generic Case

    Page(s): 2598 - 2610
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (580 KB) |  | HTML iconHTML  

    The objective of this article is to complete preliminary results from the work of Bonnard and Sugny (2009) and Sugny et al. (2007), concerning the time-minimal control of dissipative two-level quantum systems whose dynamics is governed by the Lindblad equation. The extremal system is described by a 3D-Hamiltonian depending upon three parameters. We combine geometric techniques with numerical simulations to deduce the optimal solutions. View full abstract»

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  • Output Integral Sliding Mode for Min-Max Optimization of Multi-Plant Linear Uncertain Systems

    Page(s): 2611 - 2620
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (843 KB) |  | HTML iconHTML  

    We consider the application of a min-max optimal control based on the LQ-index for a set of systems where only the output information is available. Here every system is affected by matched uncertainties, and we propose to use an output integral sliding mode to compensate the matched uncertainties right after the beginning of the process. For the case when the extended system is free of invariant zeros, a hierarchical sliding mode observer is applied. The error of realization of the proposed control algorithm is estimated in terms of the sampling step and actuator time constant. An example illustrates the suggested method of design. View full abstract»

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  • Uniformly Observable and Globally Lipschitzian Nonlinear Systems Admit Global Finite-Time Observers

    Page(s): 2621 - 2625
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (230 KB) |  | HTML iconHTML  

    There exist semi-global and finite-time converging observers for nonlinear systems that are uniformly observable and globally Lipschitzian. This was achieved with local finite-time stability theory, together with application of the technique of high-gain observers (the gain is constant). Under the same conditions, it is shown that these systems admit global finite-time observers. The proposed finite-time observers are based on a modified version of high-gain observer (now the gain is an exponential function with arbitrary growth rate). Design procedures are worked out for such observers, and a numerical example is presented to show the effectiveness of the proposed method. View full abstract»

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  • Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts

    Page(s): 2626 - 2631
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (305 KB) |  | HTML iconHTML  

    This note is concerned with the robust discrete-time iterative learning control (ILC) design for nonlinear systems with varying initial state shifts. A two-gain ILC law is considered using a 2D analysis approach. Sufficient conditions are derived to guarantee both convergence of the learning process for fixed initial condition and boundedness of the tracking error for variable initial condition. It is shown that the error data with anticipation in time can well handle the varying initial state shifts in discrete-time ILC. View full abstract»

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  • Local Mode Dependent Decentralized Stabilization of Uncertain Markovian Jump Large-Scale Systems

    Page(s): 2632 - 2637
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (250 KB) |  | HTML iconHTML  

    This technical note is concerned with the robust stabilization of a class of stochastic large-scale systems governed by a finite state Markov process. Using the method of integral quadratic constraints, a sufficient condition is developed to design decentralized stabilizing controllers which use local system states and local system operation modes to produce local control inputs. The condition is given in terms of a set of rank constrained linear matrix inequalities. The theory is illustrated by an example. View full abstract»

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  • Partially-Linear Least-Squares Regularized Regression for System Identification

    Page(s): 2637 - 2641
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (322 KB) |  | HTML iconHTML  

    In this technical note, we propose a partially-linear least-squares regularized regression (PL-LSRR) method for system identification. This method identifies a general nonlinear function as a sum of two functions which come from a linear and a nonlinear function space respectively. Both the linear and nonlinear functions can involve all regressors. Therefore, the PL-LSRR can make use of the partially-linear structure of a given system to reduce prediction errors more efficiently than exiting partially-linear identification methods. Two examples show that the PL-LSRR can reduce prediction errors and estimate the true linear expansion of the system well. View full abstract»

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  • Attitude Synchronization of a Group of Spacecraft Without Velocity Measurements

    Page(s): 2642 - 2648
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (497 KB) |  | HTML iconHTML  

    We consider the coordinated attitude control problem for a group of spacecraft, without velocity measurements. Our approach is based on the introduction of auxiliary dynamical systems (playing the role of velocity observers in a certain sense) to generate the individual and relative damping terms in the absence of the actual angular velocities and relative angular velocities. Our main focus, in this technical note, is to address the following two problems: 1) Design a velocity-free attitude tracking and synchronization control scheme, that allows the team members to align their attitudes and track a time-varying reference trajectory (simultaneously). 2) Design a velocity-free synchronization control scheme, in the case where no reference attitude is specified, and all spacecraft are required to reach a consensus by aligning their attitudes with the same final time-varying attitude. In this work, one important and novel feature (besides the non-requirement of the angular velocity measurements), consists in the fact that the control torques are naturally bounded and the designer can arbitrarily assign the desired bounds on the control torques, a priori, through the control gains, regardless of the angular velocities. Throughout this technical note, the communication flow between spacecraft is assumed to be undirected. Simulation results of a scenario of four spacecraft are provided to show the effectiveness of the proposed control schemes. View full abstract»

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  • New Expressions of 2 ,\times, 2 Block Matrix Inversion and Their Application

    Page(s): 2648 - 2653
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (198 KB) |  | HTML iconHTML  

    A 2 times 2 block matrix inversion is a tool that is frequently used in areas of control, estimation theory and signal processing. However, one of the two diagonal entries of the block matrix should be invertible to carry out a conventional block matrix inversion. In this technical note, we show that this assumption can be partially released with three new types of symbolic block matrix inversion. Also, an application example of an inverse plant model of a multi-inputs and multi-output (MIMO) plant, which cancels plant noise and disturbance, is suggested to show the effectiveness of these new types of matrix inversion. View full abstract»

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  • Dynamic Output Integral Sliding-Mode Control With Disturbance Attenuation

    Page(s): 2653 - 2658
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (227 KB) |  | HTML iconHTML  

    This technical note proposes a dynamic output feedback sliding-mode control algorithm for linear MIMO systems with mismatched norm-bounded uncertainties along with disturbances and matched nonlinear perturbations. A control law is first designed to ensure that the system behavior can satisfy the reaching and sliding condition. A scheme designed to combine the output-dependent integral sliding surface with a full-order compensator is then proposed. Through utilizing H infin control analytical technique, once the system is in the sliding mode, the proposed algorithm can guarantee robust stabilization and sustain the nature of performing disturbance attenuation when the solutions to two algebraic Riccati inequalities can be found. Finally, the feasibility of our proposed algorithm is illustrated using a numerical example. View full abstract»

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  • Asymptotic Stabilization of the Inverted Equilibrium Manifold of the 3-D Pendulum Using Non-Smooth Feedback

    Page(s): 2658 - 2662
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (291 KB) |  | HTML iconHTML  

    The 3-D pendulum consists of a rigid body, supported at a fixed pivot, with three rotational degrees of freedom; it is acted on by gravity and it is fully actuated by control forces. In , almost global stabilization of the inverted equilibrium manifold was studied using a smooth globally defined feedback. Here, we study the problem of almost global stabilization of the inverted equilibrium manifold using non-smooth feedback of angular velocity and a reduced attitude vector of the 3-D pendulum. The importance of the non-smooth feedback is that the almost global domain of attraction is a geometrically simple set that excludes the hanging attitude manifold. Unlike the closed-loop for a 3-D pendulum with a smooth controller, the closed-loop designed in this paper does not exhibit a performance constraint. These new results are based on Lyapunov analysis of the non-smooth closed-loop 3-D pendulum. View full abstract»

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  • Decentralized Stabilization of Interconnected Systems With Time-Varying Delays

    Page(s): 2663 - 2668
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (257 KB) |  | HTML iconHTML  

    This technical note establishes decentralized delay-dependent stability and stabilization methods for two classes of interconnected continuous-time systems. The two classes cover the linear case and the Lipschitz-type nonlinear case. In both cases, the subsystems are subjected to convex-bounded parametric uncertainties and time-varying delays within the local subsystems and across the interconnections. An appropriate Lyapunov functional is constructed to exhibit the delay-dependent dynamics at the subsystem level. In both cases, decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs)-based conditions under which every local subsystem of the linear interconnected delay system is robustly asymptotically stable with an gamma -level L 2-gain. Then we design a decentralized state-feedback stabilization scheme such that the family of closed-loop feedback subsystems enjoys the delay-dependent asymptotic stability with a prescribed gamma-level L 2 gain for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example. View full abstract»

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  • On the Value Functions of the Discrete-Time Switched LQR Problem

    Page(s): 2669 - 2674
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (302 KB) |  | HTML iconHTML  

    In this paper, we derive some important properties for the finite-horizon and the infinite-horizon value functions associated with the discrete-time switched LQR (DSLQR) problem. It is proved that any finite-horizon value function of the DSLQR problem is the pointwise minimum of a finite number of quadratic functions that can be obtained recursively using the so-called switched Riccati mapping. It is also shown that under some mild conditions, the family of the finite-horizon value functions is homogeneous (of degree 2), is uniformly bounded over the unit ball, and converges exponentially fast to the infinite-horizon value function. The exponential convergence rate of the value iterations is characterized analytically in terms of the subsystem matrices. View full abstract»

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  • Neighboring Extremal Solution for Nonlinear Discrete-Time Optimal Control Problems With State Inequality Constraints

    Page(s): 2674 - 2679
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (219 KB) |  | HTML iconHTML  

    A neighboring extremal control method is proposed for discrete-time optimal control problems subject to a general class of inequality constraints. The approach is applicable to a broad class of systems with input and state constraints, including two special cases where the constraints depend only on states but not inputs and the constraints are over determined. A closed form solution for the neighboring extremal control is provided and a sufficient condition for existence of the neighboring extremal solution is specified. View full abstract»

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Aims & Scope

In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering.  Two types of contributions are regularly considered

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame